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125 results about "Visual interpretation" patented technology
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VISUAL INTERPRETATION. Visual interpretation. Interpretation for Males. The histogram is a visual summary of the distribution of values. The overlay of the normal curve helps in to assessing the skewness and kurtosis. In the given study we have gender as the independent variable whereas the IQ of the participants is the dependent variable.
Method for determining volume of organic matter in reservoir rock
ActiveUS20100057409A1Simple and robust techniqueApplied quickly and inexpensivelyEarth material testingComputation using non-denominational number representationVisual interpretationHydrocotyle bowlesioides
A method for calculating the volume of various predetermined organic end-members in samples of rock at various depths in oil reservoir rock is utilized to produce one or more graphic displays that are use to interpret the data to identify, e.g., tar mats, in order to improve the efficient production of hydrocarbons from the well. Data is collected from the samples by known pyrolysis and compositional modeling methods; additional data is obtained by elemental analysis to determine weight percentages of C, H, N, S and O in the selected end-members and characterization of physical properties of representative samples of the reservoir rock, e.g., from core samples; the data is then processed in accordance with the method to provide a series of data points used to produce the graphic displays for visual interpretation.
Owner:SAUDI ARABIAN OIL CO
Automated tests to distinguish computers from humans
InactiveUS8925057B1Easy to crackDigital data processing detailsUnauthorized memory use protectionPersistence of visionVisual interpretation
Completely automated tests that exploit capabilities of human vision to tell humans apart from automated entities are disclosed herein. Persistence of vision and simultaneous contrasts are some of the properties of human vision that can be used in these tests. A video of an image is generated in colors that are distinguishable to the human eye but are not easily distinguished numerically. The image includes text manipulated such that positive image data and negative whitespace data occur at equal rates along with a noise component included in each of the video frames. Thus, raw data is made ambiguous while qualities of human visual interpretation are relied upon for extracting relevant meaning from the video.
Owner:NEW JERSEY INSTITUTE OF TECHNOLOGY
High-resolution image-based road region building change extraction method
ActiveCN106683112AAvoid interferenceImage enhancementImage analysisVisual interpretationClassification methods
The invention relates to a high-spatial resolution remote sensing image-based road region building change extraction method and device. According to the method and device, an object-oriented image processing strategy is adopted, the spectral information and spatial information (including structural indexes and spatial relationships) of images are comprehensively utilized, and a single-class classification method is adopted. In order to avoid interference (spectral similarity) on extracted results caused by ground feature classes except road regions, it is required that existing road information such as an existing road vector diagram, is provided in advance; the existing road vector diagram is adopted to extract a road region range; and newly increased buildings are extracted within the road region range. With the high-spatial resolution remote sensing image-based road area building change extraction method and device provided by the invention, time for a traditional method to obtain newly increased buildings such as illegal buildings by using image visual interpretation can be greatly decreased, efficiency can be improved, and human resources can be saved. The method and device can be used for road maintenance and monitoring business operation systems.
Owner:国交空间信息技术(北京)有限公司 +1
Plastic film mulching farmland remote sensing monitoring method based on spectrum and texture features
InactiveCN105678281AHigh precisionCharacter and pattern recognitionVisual interpretationPlastic film
The invention discloses a plastic film mulching farmland remote sensing monitoring method based on spectrum and texture features, and the method comprises the steps: S1, carrying out preprocessing of remote sensing image data of a research area; S2, building a plastic film mulching agricultural remote sensing monitoring classification system; S3, employing a Google Earth image the same as the remote sensing image data of the research area, collecting irregular polygon samples of different ground features in the classification system, and drawing the outline of a regular polygon sample of an element at a preset size through visual interpretation; S4, carrying out the separable analysis, so as to select a usable band; S5, extracting a plurality of types of texture features based on the multiband data of a remote sensing image, and extracting the texture features at three steps in four directions; S6, carrying out dimension reduction of the extracted texture feature parameters, and selecting the texture features; S7, building an input feature parameter set based on the combination of spectrum and texture features; S8, carrying out the classification of ground features of the classification system through employing a classifier. The invention proposes a new method for monitoring a plastic film mulching farmland.
Owner:INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI
Winter wheat plantation area calculation method based on winter wheat area index
ActiveCN106372592AHigh degree of automationStrong consistency of recognition resultsCharacter and pattern recognitionPicture interpretationImage resolutionVisual interpretation
The present invention relates to a winter wheat plantation area calculation method based on a winter wheat area index. The comprises: performing preprocessing of multi-date remote sensing image, and obtaining the NDVI data in a winter wheat growth period; dividing the multi-date remote sensing image into regular nets, setting weight sample central points on the regular girds, and employing a visual interpretation mode to determine the types of the samples in the girds as winter wheat and non-winter wheat; obtaining the NDVI values corresponding to the weight sample central points in the multi-date gird data, respectively calculating the NDVI mean values of the winter wheat and non-winter wheat, comparing the size of the two and setting the weight; performing weight operation of the NDVI mean values according to the weight setting result to obtaining the winter wheat area index; and employing a self-adaptive mode to extract the winter wheat area index optimal threshold value, and obtaining the plantation area of the winter wheat. The winter wheat plantation area calculation method based on the winter wheat area index can realize the high-precision calculation of the winter wheat area of the area scale of the multi-date high resolution images, the degree automation of the method is high, and the consistency of the identification result is high.
Owner:INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI
Remote sensing image mangrove forest extraction method and system based on deep convolutional neural network
ActiveCN110852225ACharacter and pattern recognitionNeural architecturesConditional random fieldData set
The invention discloses a remote sensing image mangrove forest extraction method and system based on a deep convolutional neural network, and the method comprises the steps: firstly carrying out the preprocessing of a high-resolution remote sensing image, including the atmospheric correction and research region cutting of the remote sensing image, and carrying out the waveband operation of each waveband after processing, so as to extract the priori feature information; achieving multi-band and feature information fusion by applying multi-source data fusion, and constructing a data set; training and verifying a semantic classification model ME-net built by a convolutional neural network; calling an ME-net model to realize automatic classification of the mangrove forest, and outputting a mask file in a png format, namely a classification and extraction result; and performing fine adjustment on the classification result through a long-distance conditional random field. In application of the classification model, the classification precision can reach 92.3% by expanding a data set, artificial visual interpretation can be completely replaced, and auxiliary technical support is providedfor updating of a high-precision image map and protection of a coastal region ecosystem.
Owner:湖北地信科技集团股份有限公司
Remote-sensing image multi-scale object-oriented classification method based on joint sparsity representation
ActiveCN103593853AKeep Spectral InformationKeep spaceImage analysisVisual interpretationClassification methods
The invention discloses a remote-sensing image multi-scale object-oriented classification method based on joint sparsity representation. The method includes the steps of firstly, mining a spatial characteristic of a remote-sensing image and constructing an augmentation characteristic through the combination of the spatial characteristic and a spectral characteristic, secondly, constructing a redundant dictionary by means of a training pixel sample and the augmentation characteristic, carrying out joint sparsity representation on initially segmented patches by the adoption of the redundant dictionary, thirdly, carrying out homogeneity analysis and reconstruction effect analysis on the patches on the basis of the joint sparsity representation, and finally, judging whether patch segmentation is reasonable according to analysis results of the homogeneity analysis and the reconstruction effect analysis, and carrying out classification identification on the patches meeting the requirements of the homogeneity level and the reconstruction effect. The method achieves organic combination of the segmentation process and the classification process so as to obtain proper ground object patches for classification, achieves classification identification of the remote-sensing image on the object level, can obtain a classification result meeting the requirement of visual interpretation, greatly improves interpretation precision of the remote-sensing image, and has great application value.
Owner:WUHAN UNIV
A method for detecting subcompartment forestry resources
InactiveCN109344215AThe method is efficient and feasibleDetailed and reliable result dataData processing applicationsGeographical information databasesVisual interpretationResource information
The invention discloses a method for detecting subcompartment forestry resources, comprising the following steps: step 1, checking the extraction of subcompartment; 2, collecting and processing forestry data; 3, proces that remote sensing image; 4, detect that change of the remote sensing image in the early and late period; 5, image visual interpretation; 6, supplemental investigation; 7, update that data model; 8, forestry resource information management; 9, update that output; In the first step, random sampling or typical sampling method can be used to check the extraction of subcompartments; When adopting typical sample selection, the appraised objects should be classified according to forest species, woodland type, tree species type and age group. The invention is highly effective andfeasible, and takes 3S technology and mathematical model as main means, and a forestry resource renewal method based on investigation subcompartment data, and puts forward a complete solution of annual output number of forestry resource space and attribute data, and the data detection result is objective and accurate.
Owner:山西省林业科学研究院
Night scene image denoising and enhancing processing method
InactiveCN107240081APreserve high frequency detailsEfficient separationImage enhancementImage analysisImage denoisingColor image
The invention provides a night scene denoising and enhancing processing method, relates to the field of remote sensing image processing, and solves the problems existing in an existing night scene image denoising method that visual interpretation is inconvenient, and in a process of performing enhancing processing on an image, an enhancing effect is poor and consumed time is long. Denoising processing is performed on a received original image, thereby obtaining a denoised image; Bell interpolation is performed on the denoised image, thereby obtaining a color image of three wavebands of RGB; the obtained color image of the three wavebands of RGB is converted from RGB into a YUV color domain, thereby obtaining image brightness, according to the image brightness, an image gray scale stretching coefficient is calculated, and a ratio coefficient of image brightness before and after stretching is utilized to adjust three channels of R, G and B in the same proportion, thereby obtaining an enhanced image. The binarized image generated by combination of two methods can effectively separate a foreground from a background, noise is removed, high-frequency details of the image is kept, an algorithm is simple and practicable, and thus the method is easy to directly apply in engineering treatment.
Owner:CHANGGUANG SATELLITE TECH CO LTD
Unmanned aerial vehicle image highway geological disaster identification method based on pre-training DCNN
ActiveCN110008854AImprove the efficiency of visual interpretationReduce personal safety risksCharacter and pattern recognitionNeural architecturesVisual interpretationMean-shift
The invention relates to the technical field of highway geological disaster identification, and discloses an unmanned aerial vehicle image highway geological disaster identification method based on pre-training DCNN, which comprises the following steps: S1, acquiring an unmanned aerial vehicle remote sensing image in a highway domain range, and preprocessing the unmanned aerial vehicle remote sensing image to obtain an absolutely oriented ortho-image; S2, segmenting the preprocessed unmanned aerial vehicle remote sensing image by adopting a mean shift algorithm considering image texture features; and S3, taking the segmented unmanned aerial vehicle remote sensing image data as input data, and applying the input data to the trained highway geological disaster identification model to obtaina highway geological disaster identification result. The unmanned aerial vehicle high-resolution image is adopted, the image is segmented based on the mean shift algorithm considering the texture characteristics, the segmented image unit serves as input data of the geological disaster recognition model, so the efficiency of existing geological disaster visual interpretation can be effectively improved, and data support is provided for highway field investigation and disaster risk evaluation.
Owner:CCCC SECOND HIGHWAY CONSULTANTS CO LTD
System and method for interpreting sales data through the use of natural language questions
InactiveUS20060036512A1Effective timeDigital data information retrievalCommerceDatabase queryData set
A sales management data analysis system and method for interpreting raw sales management data are provided. A plurality of natural language questions are provided, wherein each of the natural language questions correspond to at least one database query. An at least one database is queried in accordance with a selected one of the plurality of natural language questions. A particular data set is created responsive to the querying of the at least one database in accordance with the one of the plurality of natural language questions from the at least one database. And the particular data set is sent to a destination, the particular data set configured to be able to provide a particular visual interpretation thereof, wherein the particular visual interpretation is of a particular type.
Owner:IMS SOFTWARE SERVICES
Touch screen mobile terminal image quick comparison interaction method
ActiveCN108255387AReduce operating costsLess discomfortInput/output processes for data processingVisual interpretationMobile end
Owner:CHINARS GEOINFORMATICS GUANG DONG +2
Mountain vegetation vertical zone investigation monitoring method based on UAV
ActiveCN105527969AImprove representationReduce personal riskAttitude controlPosition/course control in three dimensionsVegetationImaging analysis
The present invention provides a mountain vegetation vertical zone investigation monitoring method based on a UAV. The method comprises the steps of (S1) determining an investigation time, an investigation mode and investigation precision, (S2) planning a route and carrying out automatic monitoring according to a preset route if the investigation mode is a programmed control operation mode, and manually controlling an aircraft to carrying out image capturing and obtaining monitoring data if the investigation mode is a radio remote control operation mode, (S3) carrying out space correcting processing on each image in the monitoring data, realizing the space connection of images, carrying out visual interpretation or computer automatic classification by using the spectrum and texture structure differences of different vegetation zones in a remote sensing image, identifying a vegetation vertical zone boundary, and completing the statistical measurement analysis of a vegetation vertical zone structure and result output through a geographic information system. According to the mountain vegetation vertical zone investigation monitoring method, time and labor are saved, climbing a mountain to carry out sampling positioning by investigation and monitoring personnel is not needed, an investigation result is processed by using the image analysis technology, the vertical vegetation zone identification precision is high, and the positioning is more accurate.
Owner:INST OF GEODESY & GEOPHYSICS CHINESE ACADEMY OF SCI
Spectral characteristic based remote sensing monitoring method of plastic film mulched farmland
InactiveCN105758806AHigh precisionColor/spectral properties measurementsVisual interpretationAtmospheric correction
The invention discloses a spectral characteristic based remote sensing monitoring method of plastic film mulched farmland. The spectral characteristic based remote sensing monitoring method of the plastic film mulched farmland comprises a step S1 of carrying out preprocessing on a remote sensing image, which comprises S1, radiation correction, atmospheric correction and the carrying out of inlaying and cutting processing on an image to obtain a research-area image, on the remote sensing image; a step S2 of establishing a plastic film mulched farmland remote sensing monitoring classification system, so as to distinguish the plastic film mulched farmland and other ground objects; a step S3 of collecting irregular polygonal samples of different ground object types in the classification system through visually interpreting a Google Earth image with a time phase same with that of the research-area image, and then delineating regular polygonal samples of a predetermined-size picture element anew in irregular polygons through visual interpretation; a step S4 of carrying out analysis on the separability of the different ground objects in the research-area image, so as to select a separable wave band; a step S5 of classifying the research-area image by utilizing the regular polygonal samples and using a classifier. The invention provides a new method for monitoring the plastic film mulched farmland.
Owner:INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI
Expert system for remote sensing image processing
InactiveCN104200422AImage data processing detailsKnowledge representationComputer interpretationImaging interpretation
The invention provides an expert system for remote sensing image processing. The expert system for remote sensing image processing comprises a user interface, a system interface, an inference machine, knowledge bases, a management system of the knowledge bases, a database, a database management system, a knowledge obtaining mechanism and an interpretation mechanism. The expert system earnestly and scientifically conclude and summarize and establish the knowledge bases by simulating visual interpretation experiences of a human expert, then quotes the knowledge bases to classify remote sensing data, utilizes a mode recognition method to obtain multiple characteristics of ground feature, provides evidence for remote sensing image interpretation, meanwhile applies an artificial intelligence technology, applies experiences and methods of the remote sensing image interpretation expert, simulates specific thinking process of remote sensing image visual interpretation, and performs remote sensing image interpretation to enable the computer interpretation level to reach the expert level.
Owner:JINGXI XIUMEI BIANCHENG AGRI SCI & TECH CO LTD
Northeast region paddy field classification and information extraction system and method
ActiveCN105184224AQuick identificationAccurate assessment of consumptionScene recognitionWater sourceVisual interpretation
A northeast region paddy field classification and information extraction system and a method are disclosed. The system comprises four portions of data preparation, paddy field classification, attribute addition and paddy field extraction. According to northeast-region cultivated land utilization realities, the paddy fields are divided into a ''well irrigation paddy field'' and a ''canal irrigation paddy field''. The well irrigation paddy field is the paddy field which is irrigated by underground water pumped through using a motor-pumped well. The 'canal irrigation paddy field is the paddy field which is irrigated by water sources of a canal system irrigation channel, a lake, a river, a reservoir, a pond and the like. Through a land, by using a current state data, a high-resolution remote sensing image, land reclamation data and other data, according to a canal system distribution state, classification and extraction of the 'well irrigation paddy field and the canal irrigation paddy field are realized through visual interpretation. Generally speaking, the paddy field in an irrigated area is the canal irrigation paddy field and the canal irrigation paddy field has relatively complete channel systems of a main canal, a branch canal, a lateral canal, a sublateral canal and the like; a canal system of a well irrigation paddy field area is simple and does not form a system; a surrounding electro-mechanical well is radiated outwardly; the channel is narrow; and a northeast region well irrigation paddy field area generally has a sunning water pool with a large area.
Owner:NORTHEAST AGRICULTURAL UNIVERSITY
Guided trilateral filtering ultrasonic image speckle noise removal method
ActiveCN109767400AAccurate descriptionPrevent deviationImage enhancementNormal densityPixel value difference
A guided trilateral filtering ultrasonic image speckle noise removal method comprises the steps of calculating the space domain distance weight of a guided image through a Gaussian function, and setting the standard deviation of the guided image to be increased along with increase of noise intensity; carrying out Histogram fitting on a local area of the guide image, and selecting a Fisher-Tippettprobability density function selected as a fitting function; Estimating a distribution parameter of the Tippett probability density function by adopting a maximum likelihood method, and calculating adistribution similarity weight according to the estimated parameter; calculating Pixel value difference weight of a guide image by using an exponential function, and setting a scale parameter of the guide image as an estimated Fisher-; Wherein the Tippett distribution parameters are in direct proportion change; And carrying out local iterative filtering on the ultrasonic image by using the three calculated weights, and carrying out iterative convergence to obtain the ultrasonic image with speckle noise removed. According to the method, the filtering weight value is calculated through three aspects of information of the spatial domain distance, the pixel value difference and the distribution similarity, speckle noise can be effectively reduced, meanwhile, detail and edge information of theimage can be better reserved, and therefore visual interpretation of the ultrasonic image is enhanced.
Owner:CHINA THREE GORGES UNIV
Remote sensing earthquake damage information extracting and digging method based on pixels
InactiveCN101788685ASolve the problems of heavy workload and long investigation cycle for manual interpretationImprove efficiencyImage analysisSeismic signal processingVisual interpretationWorkload
The invention discloses a remote sensing earthquake damage information extracting and digging method based on pixels. The method comprises the following steps of: firstly, automatically finding a change area by a spectrum variance and main component integration method according to the remote sensing images of different time phases before and after earthquake; then, segmenting the change image by using a dual-threshold area growth algorithm to obtain change information binary images; finally, carrying out artificial visual interpretation on the segmented binary images of the change area, and extracting the earthquake damage information. The invention solves the problems that the workload of artificial interpretation on the earthquake change information is large and the survey period is long, enhances the efficiency, and simultaneously guarantees the sufficient precision.
Owner:中国土地勘测规划院
Method for determining volume of organic matter in reservoir rock
ActiveUS8492153B2Simple and robust techniqueApplied quickly and inexpensivelyEarth material testingComputation using non-denominational number representationVisual interpretationHydrocotyle bowlesioides
Owner:SAUDI ARABIAN OIL CO
High-resolution remote sensing image fusion method based on linear Bayesian estimation
InactiveCN103576164AImage enhancementElectromagnetic wave reradiationRemote sensing image fusionVisual interpretation
The invention belongs to the technical field of remote sensing image processing, and particularly discloses a high-resolution remote sensing image fusion method based on linear Bayesian estimation. According to the high-resolution remote sensing image fusion method, an observation model between a high-resolution multi-spectrum image and a low-resolution multi-spectrum image and an observation model between the high-resolution multi-spectrum image and a full-color image are introduced, and the two observation models are connected to form a Bayesian linear model. Estimation on the high-resolution multi-spectrum image in the linear minimum mean square error sense is obtained by applying the Bayes Gauss-Markov theorem. According to the high-resolution remote sensing image fusion method, space details can be strengthened, the spectral characteristics are well kept, the performance of the high-resolution remote sensing image fusion method is better than the performance of a traditional HIS method, a traditional PCA method, a traditional wavelet transformation method, an existing Nishii method based on statistic parameter estimation and an existing Hardie method based on statistic parameter estimation, and new and effective technical supports are provided for improving the visual interpretation accuracy of a remote sensing image, the information definition and the reliability.
Owner:上海知贤认证有限公司
Method and platform for dynamic monitoring of typical ground features in mining based on multi-source remote sensing data fusion and deep neural network
PendingCN111742329AImprove spatial resolutionImprove computing efficiencyCharacter and pattern recognitionNeural architecturesVisual interpretationDynamic monitoring
Owner:ANHUI ZHONGKE INTELLIGENT PERCEPTION BIG DATA IND TECH RES INST CO LTD
Method for detecting marine moving target of thermal infrared remote sensing image based on multi-feature fusion
ActiveCN106651880AConvenient inspectionImprove accuracyImage enhancementImage analysisThermal infrared remote sensingVisual interpretation
The invention discloses a method for detecting a marine moving target of a thermal infrared remote sensing image based on multi-feature fusion. The method comprises the following steps of carrying out sea-land segmentation on a thermal infrared image to obtain a sea area image; utilizing a priori segmentation parameter to carry out multi-scale segmentation on the sea area image to obtain an object; extracting brightness and geometrical characteristics of the object obtained by segmentation; and carrying out decision tree classification on a segmentation object through corresponding classification rules which are obtained by respectively carrying out contrast training on the obtained brightness and the geometrical characteristics of the segmentation object in order to realize detection of the marine moving target. The method utilizes the thermal infrared remote sensing image as a data source, so that the defects of failure of a visible / near-infrared multispectral image at night, difficulty in visual interpretation of an SAR image, complicated processing steps and the like in the existing method can be made up to be beneficial to detection of a detection result, so that the accuracy of information is further improved; the obtained temperature information is extracted based on the marine moving target obtained by detection to be beneficial to judgement of state of the marine moving target.
Owner:CAPITAL NORMAL UNIVERSITY +1
Deep learning satellite data cloud detection method supported by hyperspectral data
ActiveCN110427818AHigh degree of automationAvoid askingSpectrum investigationScene recognitionVisual interpretationSpectral response function
The invention discloses a deep learning satellite data cloud detection method supported by hyperspectral data. The method comprises the following steps: selecting enough cloud and clear sky pixels toconstruct a hyperspectral data sample library, and performing analog computation on the hyperspectral pixel sample library according to parameters such as a spectral response function and a waveband width of a to-be-detected sensor to obtain a cloud and clear sky surface pixel library of the to-be-detected sensor; based on a Keras deep learning framework, designing a deep BP neural network for cloud detection, inputting multispectral sample data obtained through simulation into the network for training and learning, and obtaining a multispectral sensor cloud detection rule based on spectral characteristics; based on a Markov random field model, optimizing a cloud detection result by utilizing an iterative condition mode algorithm, and removing a part of misclassification and misclassification errors of cloud detection. According to the method, various sensor data are selected and compared with a cloud coverage result of artificial visual interpretation for analysis, and the result shows that the algorithm achieves a better cloud detection effect and can meet the requirements of data application for cloud detection.
Owner:青岛星科瑞升信息科技有限公司
Method for processing remote sensing images based on tasseled cap transformation
InactiveCN102306372AEstimated ageEstimated changeGeometric image transformationRotation methodVisual interpretation
The invention discloses a method for processing remote sensing images based on tasseled cap transformation. The method comprises the following steps of: (1) selecting at least 10 representative remote sensing images, and performing radiometric calibration and atmospheric correction to acquire the actual earth surface reflectivity; (2) calculating a principle component transformation coefficient of each remote sensing image respectively, and fitting the principle component transformation coefficient through a least square method to obtain a new coefficient, namely a primitive axis; (3) setting an angle for the primitive axis by rotating to obtain a tasseled cap transformation coefficient axis, wherein a rotation method comprises selecting set number sampling points respectively from each image on the basis of TM tasseled cap transformation characteristics and rotating the primitive axis through visual interpretation, and the distribution of the rotated sampling points is the same as the TM tasseled cap transformation characteristics; and (4) according to the tasseled cap transformation coefficients obtained in the step (3), performing linear transformation on multi-spectrum remote sensing images to obtain an imaging result. The invention provides the method for processing the remote sensing images based on the tasseled cap transformation, and the method provided by the invention is used for extracting image physical characteristics.
Owner:ZHEJIANG UNIV
Plastic film mulching farmland remote sensing monitoring method based on texture features
InactiveCN105678280AHigh precisionCharacter and pattern recognitionVisual interpretationPlastic film
The invention discloses a plastic film mulching farmland remote sensing monitoring method based on texture features, and the method comprises the steps: S1, carrying out preprocessing of remote sensing image data; S2, building a plastic film mulching agricultural remote sensing monitoring classification system; S3, collecting irregular polygon samples of different ground features in the classification system through visual interpretation, and drawing the outline of a regular polygon sample of an element at a preset size through visual interpretation; S4, extracting a plurality of types of texture features based on the multiband data of a remote sensing image through employing a gray co-occurrence matrix method, and extracting the texture features; S5, carrying out dimension reduction of the extracted texture feature parameters S6, constructing input features in four directions based on the selected texture features serving as a classification feature parameter set; S6, constructing the input features in four directions; S7, carrying out the classification of ground features of the classification system through employing a classifier. The invention proposes a new method for monitoring a plastic film mulching farmland.
Owner:INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI
Method and apparatus for enhancing a digital image
ActiveUS20090219407A1Easy visual interpretationEnhance the imageTelevision system detailsImage enhancementSpectral bandsDigital number
Owner:MAXAR INTELLIGENCE INC
Double-path convolutional neural network remote sensing classification method taking spatial neighborhood relationship into account
ActiveCN107967454AReduce distractionsImprove classification accuracyScene recognitionGeographical information databasesNerve networkVisual interpretation
The invention discloses a double-path convolutional neural network remote sensing classification method taking a spatial neighborhood relationship into account. The double-path convolutional neural network remote sensing classification method comprises the steps of: data acquisition; data preprocessing; thematic map production; multi-scale segmentation; visual interpretation; first-order neighborhood acquisition; experimental sample set selection; patch size selection; training data generation; mat format conversion; convolutional neural network structure construction; subject single-path neural network training; first-order neighborhood single-path neural network training; complementarity analysis; and double-path convolutional neural network training taking the spatial neighborhood relationship into account. The invention aims to provide a method for regarding a subject and a first-order neighborhood of the subject as input image data on the same scale, realizing the enhancement of sample information through increasing neighborhood information of samples and reducing interference caused by other types of samples, so as to realize the improvement of classification precision and provide a reference for classification decision-making.
Owner:WUHAN UNIV OF TECH
Surface form deviation measurement method of flat optical element
InactiveCN101672631AImprove adaptabilityHigh measurement accuracyUsing optical meansNeural learning methodsDigital signal processingVisual interpretation
The invention discloses a surface form deviation measurement method of a flat optical element. Firstly, a camera collects a standard sample image data and sends the collected standard sample image data to DSP via a USB interface for digital signal processing; the processed image data trains a BP neural network to determine the adopted BP neural network; because the camera collects the interferencefringe image data of a measured flat optical element, the camera sends the collected image data to the DSP via the USB interface for digital signal processing, and the obtained measuring data is sentto a determined BP neural network for calculation; the BP neural network outputs a surface form deviation value and sends into a DSP cache region; and the DSP sends the surface form deviation value to a display device for displaying. Because a manipulator can conveniently observe the interference fringe image and adjust the light path, detection cost is lowered; the measuring result is not affected by a person of visual interpretation, thus effectively improving measurement precision.
Owner:SHANGHAI SECOND POLYTECHNIC UNIVERSITY
Method for extracting and simplifying three-dimensional road model
PendingCN112307553AGuaranteed Extraction EffectReduce processing difficultyGeometric CADDesign optimisation/simulationComputer graphics (images)Algorithm
The invention discloses a method for extracting and simplifying a three-dimensional road model, which comprises the following steps of: obtaining a multi-patch reference surface in a model of road elements to be extracted, constructing a hexagonal bounding box and orthogonally projecting the hexagonal bounding box to two dimensions, and greatly simplifying the operation difficulty of road sketching in a complex three-dimensional scene under the condition of retaining color and depth information, and the corresponding space and texture coordinates are obtained according to the road extraction area, so that the effect of automatically constructing the road model is achieved. According to the method, the original manual visual interpretation work is replaced by a computer space resolving technology, so that the extraction efficiency and accuracy of the road elements in a large-scale three-dimensional scene are effectively ensured.
Owner:ZHEJIANG LAB
Landslide recognition knowledge base establishment method and device, electronic equipment and storage medium
PendingCN113989637AHigh data accuracyImprove accuracyCharacter and pattern recognitionData setVisual interpretation
Owner:AEROSPACE INFORMATION RES INST CAS +1
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